The increased incidence of diabetic retinopathy (DR) and the legacy effect associated with it has raised a great concern toward the need to find early diagnostic and treatment strategies. Identifying alterations in genes and microRNAs (miRNAs) is one of the most critical steps toward understanding the mechanisms by which a disease progresses, and this can be further used in finding potential diagnostic and prognostic biomarkers and treatment methods. We selected different datasets to identify altered genes and miRNAs. The integrative analysis was employed to find potential candidate genes (differentially expressed and aberrantly methylated genes that are also the target of altered miRNAs) and early genes (genes showing altered expression and methylation pattern during early stage of DR) for DR. We constructed a protein-protein interaction (PPI) network to find hub genes (potential candidate genes showing a greater number of interactions) and modules. Gene ontologies and pathways associated with the identified genes were analyzed to determine their role in DR progression. A total of 271 upregulated-hypomethylated genes, 84 downregulated-hypermethylated genes, 11 upregulated miRNA, and 30 downregulated miRNA specific to DR were identified. 40 potential candidate genes and 9 early genes were also identified. PPI network analysis revealed 7 hub genes (number of interactions >5) and 1 module (score = 5.67). Gene ontology and pathway analysis predicted enrichment of genes in oxidoreductase activity, binding to extracellular matrix, immune responses, leukocyte migration, cell adhesion, PI3K-Akt signaling pathway, ECM receptor interaction, etc., and thus their association with DR pathogenesis. In conclusion, we identified 7 hub genes and 9 early genes that could act as a potential prognostic, diagnostic, or therapeutic target for DR, and a few early genes could also play a role in metabolic memory phenomena.